Useful tips for everyday
How do stack algorithms work? Stacking or Stacked Generalization is an ensemble machine learning algorithm. The benefit of stacking is that it can harness the…
What is the relationship between reinforcement learning and Markov decision process? So roughly speaking RL is a field of machine learning that describes methods aimed…
How does TD learning differ from the Monte Carlo method? The main difference between them is that TD-learning uses bootstrapping to approximate the action-value function…
What does EXP lambda mean? If (the Greek letter “lambda”) equals the mean number of events in an interval, and (the Greek letter “theta”) equals…
How does lasso differ from ridge regression? Lasso regression stands for Least Absolute Shrinkage and Selection Operator. It adds penalty term to the cost function.…
Why do we need intercept in linear regression? Most multiple regression models include a constant term (i.e., the intercept), since this ensures that the model…
How to test the significance of a categorical variable? For categorical variables in the logistic regression model only the pooled statistics for each separate level…
What does it mean to residualize a variable? Partial regression coefficients are the most important parameters of the multiple regression model. They measure the expected…
When to choose a multiplicative model or additive model? Choose the multiplicative model when the magnitude of the seasonal pattern in the data depends on…
How percentages can be misleading? Percent change is misleading because it’s hard to know if the percentage was calculated using the original numbers or the…